We will use the pared down dataset created earlier.
flu_visits =
read_csv("./ed_flu_tidy.csv")
## Parsed with column specification:
## cols(
## extract_date = col_date(format = ""),
## date = col_date(format = ""),
## mod_zcta = col_double(),
## total_ed_visits = col_double(),
## ili_pne_visits = col_double(),
## ili_pne_admissions = col_double(),
## pct_visits = col_double(),
## pct_adm = col_double()
## )
Pull in zip code/borough tibble from the web.
url = "https://www.health.ny.gov/statistics/cancer/registry/appendix/neighborhoods.htm"
zip_boro_html = read_html(url)
zip_boro_df =
zip_boro_html %>%
html_nodes(css = "table") %>%
html_table(header = TRUE) %>%
colnames()
as_tibble(rownames = c("boro", "neighborhood", "zip_code"))
mutate(
boro = as.character(Borough),
neighborhood = as.character(Neighborhood),
zip_code = as.character("Zip Codes")
) %>%
select(-Neighborhood) %>%
janitor::clean_names()
Create a map using plotly.
flu_visits %>%
mutate(text_label = str_c(
"Date: ", date,
"\n% ILI Visits: ", pct_visits,
"\n% ILI Admissions: ", pct_adm)) %>%
plot_ly(
x = ~date, y = ~total_ed_visits, color = ~mod_zcta, text = ~text_label,
alpha = 0.3, type = "scatter", mode = "markers"
)
## Warning: `arrange_()` is deprecated as of dplyr 0.7.0.
## Please use `arrange()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.